Big data is a term commonly used by the press and analysts yet few people really understand what it means or how it might affect them. At it’s core, Big Data represents a very tangible pattern for IT workers and demands a plan of action. For those who understand it, the ability to create an actionable plan to use the knowledge tied up in the data can provide new opportunities and rewards.

Let’s first solidify our understanding of Big Data. Big Data is not about larger ones and zeros nor is it a tangible measurement of the overall size of data under your stewardship. Simply stated, one does not suddenly have “big data” when a database grows past a certain size. Big Data is a pattern in IT. The pattern captures the fact a lot of data collections that contain information related to an enterprise’s primary business are now accessible and actionable for that enterprise. The data is often distributed and in a variety of formats which makes it hard to curate or use, hence Big Data represents a problem as much as it does a situation. In many cases, just knowing that data even exists is a preliminary problem that many IT workers are finding hard to solve. The peripheral data is often available from governments, sensor readouts, in the public domain or simply made available from API’s into other organizations data. How do we know it is there, how can we get at it and how can we get the interesting parts out are all first class worries with respect to the big data problem.

To help illustrate the concepts involved in Big Data, we will use a hospital as an example. A hospital may need to plan for future capacity and needs to understand the aging patterns from demographics data that is available from a national census organization in the country they operate in. It also knows that supplementary data is available in terms of finding out how many people search for terms on search engines related to diseases and the percentage of the population that smokes, is not living healthy lifestyles and participates in certain activities. This may have to be compared to current client lists and the ability to predict health outcomes for known patients of a specific hospital, augmented with the demographic data from the larger surrounding population.

The ability to plan for future capacity at a health institute may require that all of this data plus numerous other data repositories are searched for data to support or disprove the hypothesis that more people will require more healthcare from the hospital in ten years.

Another situation juxtaposed to illustrate other aspects to Big Data could be the situation whereby a single patient arrives at the hospital with an unknown disease or infection. Hospital workers may benefit from knowing the patients background yet may be unaware of where that data is. Such data may reside in that patients social media accounts such as FourSquare, a website that gamifies visits to businesses. The hospital IT workers in this scenario need to find a proverbial needle in a haystack. By searching across all known data sources, the IT workers might be able to scrape together a past history of the patient’s social media declarations which might provide valuable information about a person’s alcohol drinking patterns (scraped from FourSquare visits to licensed establishments), exercise data (from a site like socialcyclist.com) and data about their general lifestyle (stripped from Facebook, Twitter and other such sites). When this data is retrieved and combined with data from LinkedIn (data about the patients business life), a fairly accurate history can be established.

By combining photos from Flickr and Facebook, Doctors could actually see the physical changes in the way a patient looks over time.

The last example illustrates that the Big Data pattern is not always about using large amounts of data. Sometimes it involves finding the smaller atoms of data from large data collections and finding intersections with other data. Together, these two hospital examples show how Big Data patterns can provide benefits to an enterprise and help them carry out their primary objectives.

To gain access to the data is one matter. Just knowing the data is available and how to get at it is a primary problem. Knowing how the data relates to other data and being able to tease out knowledge from each data repository is a secondary problem that many organizations are faced with.

Some of our staff members recently worked on a big data project for the United States Department of Energy related to Geothermal prospecting. The Big Data problem there involved finding areas that may be promising in terms of being able to support a commercially viable geothermal energy plant that must operate for ten or more years to provide a valid ROI for investors. Once the rough locations are listed, a huge amount of other data needs to be collected to help determine the viability of a location.

Some examples of the other questions that need to be answered with Big Data were:

What is the permeability of the materials near the hot spot and what are the heat flow capabilities?

How much water or other fluids are available on a year round basis to help collect thermal energy and turn it into kinetic energy?

How close is the point of energy production to the energy consumption?

Is the location accessible by current roads or other methods of transportation?

How close is the location to transmission lines?

Is the property currently under any moratoriums?

Is the property parkland or other special use planning?

Does the geothermal potential overlap with existing gas and oil claims or other mineral rights or leases?

Etc…

All of this data is available, some of it in prime structured digital formats and some of it not even in digital format. An example of non-digital format might be a drill casing stored in a drawer in the basement of a University that represents the underground materials near the heat dome. By studying its’ structure, the rate of heat exchange through the material can provide clues about the potential rate of thermal energy available to the primary exchange core.

In order to keep track of all the data that exists and how to get at it, many IT shops are starting to use graphs and graph database technologies to represent the data. The graph databases might not store the actual data itself, but they may store the knowledge of what protocols and credentials to use to connect to the data, what format the data is in, where the data is located and how much data is available. Additionally, the power of a graph database is that the database structure is very good at tracking the relationships between clusters of data in the form of relationships that capture how the data is related to other data. This is a very important piece of the puzzle.

The conclusion of the introduction post to Big Data is that Big Data exists already. It is not something that will be created. The new Big Data IT movement is about implementing systems to track and understand what data exists, how it can be retrieved, how it can be ingested and used and how it related (semantically) to other data.

The real wins will be when systems can be built that can automatically find and use the data that is required for a specific endeavor in a real time manner. To be truly Big Data ready is going to require some planning and major architecture work in the next 3-5 years.

For those of you who spend time caring for patients, rather than keeping up to date on every proposed regulation that comes out of CMS, here are the highlights of one that directly affects you. On April 15, CMS published a proposed rule that makes dramatic changes in Stage 2 of Meaningful Use (MU). Essentially, Stage 2 as we knew it, no longer exists. The final rule, when it is published later this year, will define a new Stage 2 that will be in effect from 2015 through 2017, and possibly longer. The bad news is that everyone impacted by MU is in a holding pattern waiting for the final rule. Once it is published, we will all have to scramble to meet the new requirements before the end of 2015. The good news is that the proposed attestation period for 2015 will be any continuous 90-day period for all eligible professionals (EPs), as opposed to the full year. The proposed rule also addresses many of the concerns we have raised about the excessive reporting requirements contained in the old Stage 2 specification. If you were planning to skip the MU program this year due to the excessive burden of Stage 2, you may want to reconsider. While the final rule will have changes based on comments submitted on the proposed rule, we expect that, overall, it will be similar to the proposed rule.

Here are some of the Highlights:

EHR Reporting Period in 2015 and 2016

First, CMS proposes to align the definition of an EHR reporting period with the calendar year for all types of providers beginning in 2015 and continuing through 2016 and beyond. Specifically, beginning in 2015, this proposal would change the EHR reporting period for eligible hospitals (EHs) and critical access hospitals (CAHs) from a period based on the fiscal year to one based on the calendar year, and thus aligning it with the reporting period for individual EPs.

Second, for 2015 and 2016, CMS proposes to allow all new participants in the EHR Incentive Program (including new EPs, EHs, and CAHs) to attest to meaningful use for an EHR reporting period of any continuous 90-day period within the calendar year. In addition, for 2015 only, all EPs (regardless of their prior participation in the program) will be able to attest to an EHR reporting period of any continuous 90-day period within the calendar year. So, if you have not begun reporting for this year, you still have time! However, starting in 2016, all returning participants will need to use an EHR reporting period of a full calendar year (i.e., from January 1, 2016 through December 31, 2016).

Finally, CMS proposes changes to many of the individual objectives and measures for Stage 2 of meaningful use, including the following:

Changing the threshold from the Stage 2 Objective for Patient Electronic Access measure number 2[1] from “5 percent” to “equal to or greater than 1″. CMS acknowledges that external factors beyond EPs control can impact their ability to meet this measure. Practices have been reporting since the start of Stage 2 that convincing 5% of patients to perform the specified action is difficult or impossible.

Changing the threshold of the Stage 2 Objective Secure Electronic Messaging[2] from being a percentage-based measure, to a yes-no measure stating the “functionality fully enabled”. As with the patient electronic access measure, practices report that convincing 5% of patients to perform the specified action is difficult or impossible.

Consolidating the four Stage 2 public health reporting objectives into one objective with multiple measure options following the structure of the Stage 3 Public Health Reporting Objective. This provides EPs with much more flexibility in selecting public health reporting objectives that make sense for their practices and for which the reporting capabilities exist.

Essentially, Stage 2 has been completely re-worked to respond to complaints raised by many, and to align it with what is expected in Stage 3. Stay tuned for announcements regarding final CMS decisions on Stage 2 modifications and on Stage 3 requirements.

I have been drawn to social media (SM) both personally and professionally for many years now, but I still feel like an outlier in using it professionally. There have been ASCO education sessions on this topic, educational book articles, publications, and the like, but many of these take the approach that people don’t really understand SM and what it offers.

I fear that there is a different issue, that perhaps many health care professionals do think that they understand SM and that they have consciously decided not to use it professionally. Maybe they signed up for Twitter with their children’s help and found their feeds rapidly filled with tweets about Kim Kardashian, or they got Facebook friend requests from patients and quailed at the potential conflict of interest. Perhaps they mentioned it to colleagues or their chairperson and discovered that SM was dismissed or perhaps actively discouraged as something that had little benefit to a professional career. Instead of another lecture on how to sign up for SM, I thought I would share my experience, along with specific examples of how SM has directly led to professional benefits.

There is nothing inherently good or bad about SM. To put it simply, social media is media that is social; e.g., you can use it to interact with other people. Normal media is one direction only, to be received by you. You can yell at your television during the presidential debates, but Hillary, Bernie, Ted, and Donald can’t hear you. Social media allows you to interact with whoever is providing the information. If you disagree, please let me know in the comments below.

I first saw the potential of SM about 8 years ago, when I met Dr. Jack West, who was looking for oncologists to help provide content for his patient education website. I found that I could write blogs on lung cancer trials and get immediate feedback from patients and other doctors on my thoughts. More importantly, I could interact on the discussion boards with patients with lung cancer from all over the globe who wanted to understand their disease better, and I could help them make sense of a world turned upside down.

I was amazed at both the profound reach and the immediacy of it, and I was able to build somewhat of a professional reputation in lung cancer very early in my career by talking about issues in real time without being constrained by publication paywalls and schedules. I distinctly remember one reception at the ASCO Annual Meeting, where a senior investigator I barely knew walked up to me out of the blue and told me that she liked my take on her research, leading to a (small) role for me in a grant application she was submitting.

I have always been a news junkie, but joining Twitter in 2010 opened up a whole new dimension. At first I simply “followed” the few early-adopting oncology experts but didn’t think much of it. Over time, however, I realized that just about everything I was interested in was out there to be discovered in almost real time. I followed the beat reporters for my favorite sports teams and reporters from the New York Times and Washington Post, and was able to get (free) news around the clock while other people were waiting for the morning paper to learn anything new.

first saw the potential of SM about 8 years ago, when I met Dr. Jack West, who was looking for oncologists to help provide content for his patient education website. I found that I could write blogs on lung cancer trials and get immediate feedback from patients and other doctors on my thoughts. More importantly, I could interact on the discussion boards with patients with lung cancer from all over the globe who wanted to understand their disease better, and I could help them make sense of a world turned upside down.

I was amazed at both the profound reach and the immediacy of it, and I was able to build somewhat of a professional reputation in lung cancer very early in my career by talking about issues in real time without being constrained by publication paywalls and schedules. I distinctly remember one reception at the ASCO Annual Meeting, where a senior investigator I barely knew walked up to me out of the blue and told me that she liked my take on her research, leading to a (small) role for me in a grant application she was submitting.

I have always been a news junkie, but joining Twitter in 2010 opened up a whole new dimension. At first I simply “followed” the few early-adopting oncology experts but didn’t think much of it. Over time, however, I realized that just about everything I was interested in was out there to be discovered in almost real time. I followed the beat reporters for my favorite sports teams and reporters from the New York Times and Washington Post, and was able to get (free) news around the clock while other people were waiting for the morning paper to learn anything new.

In the past year, my latest SM endeavor has been blogging on ASCO Connection. A blog post is just an essay on a topic you feel strongly about, and ASCO Connection is nice enough to put the words up for colleagues to read. It is a wonderful feeling to have something to say and to be able to write it down and put it out there for others to see and comment on, and — given the size of ASCO’s membership — this platform reaches quite a few people.

So why get involved in SM as an oncology professional? Aside from the benefits of gathering information, it gets your name out there, especially early in your career. Many senior oncologists don’t think they need to be on SM, leaving a huge void that still is very open for junior people to fill. While professionals might not be on SM, patients, organizations, and traditional media are. When you are one of only a dozen experts in your field active on Twitter, you have a disproportionate influence. My involvement in GRACE led to numerous opportunities and connections, including an invitation to join ASCO’s Integrated Media and Technology Committee and opportunities to work with ASCO University online. In one interesting twist, a blog post I wrote on the stigma of tobacco and lung cancer led to an invitation to participate in a Congressional Briefing on Capitol Hill.

These are just a few examples from my own experience that I hope allow you to see some of the potential of SM to benefit your life and career. The full potential of oncology social media can’t be realized until a critical mass of professionals is actively participating, but many continue to resist. I strongly encourage you, especially junior professionals, to set up a Twitter account and start to follow some people you know. If you gave up on it in the past, try again, and don’t be afraid to ask for help if you feel you aren’t getting what you want out of it. Try it, and I think you’ll see the potential just as I did.

Sharing your scoops to your social media accounts is a must to distribute your curated content. Not only will it drive traffic and leads through your content, but it will help show your expertise with your followers.

Integrating your curated content to your website or blog will allow you to increase your website visitors’ engagement, boost SEO and acquire new visitors. By redirecting your social media traffic to your website, Scoop.it will also help you generate more qualified traffic and leads from your curation work.

Distributing your curated content through a newsletter is a great way to nurture and engage your email subscribers will developing your traffic and visibility.
Creating engaging newsletters with your curated content is really easy.